On Research

I am marching towards Synergetic & Holistic Intelligence.

My long term goal is to advance AI research and technologies in interrelated fields such as computer vision, machine learning, language understanding and robotics, to build intelligent systems, either virtual or embodied, to facilitate understanding multiple sensory inputs, to gain actionable insights from perception to cognition, to solve important real-world problems and to better serve our human race.

In the medium term, I am putting more emphasis on computer vision, machine learning and their applications, with a strong focus on accurate and efficient understanding of various types of objects and activities from sensory inputs such as images and videos. Over the past few years, I have explored a wide range of topics towards accurate and efficient visual understanding: from image-level classification, to instance-level object detection, to video-level detection and tracking, and more recently to spatio-temporal activity recognition and pixel-level segmentation etc. My team and I have been lucky to have won some international AI competitions and set new state-of-the-arts on major computer vision benchmarks. I am also fortunate to have been working on a broad spectrum of applied research projects with more than $10 million support, from research assistant, to team leader, and PI/Co-PI, with collaborators and support from industry, academic units and government agencies. This enables me to understand the true depth of challenges arose from real-world data and problems, or even in collaboration, management and technology transfer.

To emphasize, my current research focuses on accurate & efficient visual understanding and deep learning for AI systems & application, in particular I have recently worked in:

    • Computer Vision: classification, object detection, segmentation, activity recognition, etc.

    • Machine Learning: deep learning, weakly-supervised learning, transfer learning, efficient learning, etc.

    • AI Systems & Applications for Science, Engineering Education, Agriculture, Medicine, Finance, Art, Transportation, etc.

My research activities include multiple aspects to solve such problems and to advance AI research: projects, papers, competitions, organizing workshops, teaching and training students etc.

Please find more publication and technical reports on Google Scholar. Some of our codes and datasets are available at GitHub.

Papers etc. are also organized by three main themes here:

Abbreviations: [C]: Conference; [J] Journal; [W] Workshop; [TR]: Technical Report; [P]: Patent; [Comp]: Competition; [Proj]: Project; [Org] Program Organization; [SOTA]: State-of-the-art (at the time of publication).



2021 (CVPR x 3, AAAI x 3, TPAMI ...)

2020 (CVPR x 5, MICCAI, TPAMI, CCR, MLSys, AAAI ...)

2019 (ICCV x 2, CVPR x 2, AAAI x 2, BMVC ...)

2018 (ECCV x 2, CVPR ...)

Before 2018 (have mainly worked on interdisciplinary research projects and several competitions)


  • [Proj] Collaborative research on multimedia with Blender Lab at UIUC (2020-Present)

  • [Proj] Collaborative research on visual reasoning with IBM Research (2020-Present)

  • [Proj] Automated Cerebral Aneurysm Segmentation & Applications in Resident Training, sponsored by Jump ARCHES (2020-Present)

  • [Proj] Automated Retinopathy of Prematurity Detection and Analysis, sponsored by Jump ARCHES (2020-Present)

  • [Proj] A Large-scale Dataset for Text Segmentation, Sponsored by Adobe Research (2020-Present)

  • [Proj] Cement Phase Segmentation, collaborated with UIUC Civil Engineering (2018-2020)

  • [Proj] Multiphoton Image Analysis for Cancer Diagnosis, sponsored by Mayo Clinic & UIUC (2018-2019)

  • [Proj] AI for Education, sponsored by New Oriental Education Technology (2018-2019)

  • [Proj] Deep Pattern Analysis in Agricultural Images, sponsored by IntelinAir (2018-2020)

  • [Proj] Deep Intermodal Video Analytics (DIVA), sponsored by IARPA, (2017-2021)

  • [Proj] Intelligent Learning Advisor, sponsored by IBM Research (2017-2021)

  • [Proj] Multi-Task Learning for Medical Image Analysis, sponsored by Siemens (2016-2019)

  • [Proj] Multi-modal Medical Image Understanding, sponsored by Jump ARCHES (2016-2018)

  • [Proj] Deep Learning in Financial Modeling and Strategy, sponsored by Jump Trading (2015-2018)

  • [Proj] Galaxy Classification, collaborated with UIUC Astronomy (2014-2015)

  • [Proj] Gravitational Lens Detection, collaborated with UIUC Astronomy (2014-2015)


  • [Comp] IEEE/ACM DAC System Design Contest 1st Place (2019)

  • [Comp] NIST/IARPA TRECVID Activity Recognition Challenge 1st Place for both tracks (2018)

  • [Comp] Visual Relationship Detection - Google AI Open Images Challenge, Silver Medal (2018)

  • [Comp] Nvidia AI City Challenge 3rd Place (2018)

  • [Comp] CVPR Look Into Person Challenge 1st Place for all three tracks(2018)

  • [Comp] ImageNet Video Object Detection and Tracking Challenge 2nd Place for all four tracks(2017)

  • [Comp] Nvidia AI City Challenge 1st Place (2017)

  • [Comp] ImageNet Video Object Detection Challenge 3rd Place (2015)

  • [Comp] Galaxy Zoo - The Galaxy Challenge on Kaggle, Silver Medal (2014)